Methods and systems for recalling second party interactions with mobile devices

ABSTRACT

Systems and methods are presented for identifying individuals through facial recognition, voice recognition, or the like, recalling past recorded conversations with the identified individuals, and recording and inventorying conversations with the individuals with mobile devices. In some embodiments, a method is presented. The method may include identifying, at a device, an individual through facial recognition, voice recognition, or a unique RFID. The method may also include recording a conversation with the identified individual, and recalling past relevant recorded conversations based on the identification of the individual, and transmitting the recording of the conversation to a display system configured to display the recording of the event.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/252,551 filed on Aug. 31, 2016, which is a continuation of U.S.patent application Ser. No. 14/484,157, filed on Sep. 11, 2014, whichapplications are incorporated herein by reference in their entirety.

TECHNICAL FIELD

The subject matter disclosed herein generally relates to technology in asocial communication context. In some example embodiments, the presentdisclosures relate to systems and methods for identifying individualsthrough facial recognition, voice recognition, or the like, recallingpast recorded conversations with the identified individuals, andrecording conversations with the individuals with mobile devices.

BRIEF DESCRIPTION OF THE DRAWINGS

Some embodiments are illustrated by way of example and not limitation inthe figures of the accompanying drawings.

FIG. 1 is block diagram illustrating a mobile device suitable forrecording conversations or events and recalling said conversations orevents at a later time, according to some example embodiments.

FIG. 2 is a set of images of various wearable devices suitable forrecording conversations or events and recalling said conversations orevents at a later time, according to some example embodiments.

FIG. 3 is an example scenario for identifying an individual, andrecording a conversation with that individual with a mobile device,according to some example embodiments.

FIG. 4 is an example scenario for identifying an individual, recording aconversation with the individual, and replaying the recordedconversation through a third party device, according to some exampleembodiments.

FIG. 5 is another example scenario for identifying an individual,recording a conversation with that individual, and transmitting theconversation to a third party device, where it may later be referenced,according to some example embodiments.

FIG. 6 is an example embodiment of a repository for storing anddisplaying recordings of conversations.

FIG. 7 is an example scenario for identifying an individual anddisplaying relevant information related to that individual, based onautomatic recognition, with a mobile device.

FIG. 8 is a flowchart illustrating example operations for: identifyingan individual; recalling, based on automatic recognition, relevantrecordings of conversations with that individual; recording theconversation with the individual; and transmitting the recording to asystem configured to replay the recording of the conversation with amobile device, according to some example embodiments.

FIG. 9 is a block diagram illustrating components of a machine,according to some example embodiments, able to read instructions from amachine-readable medium and perform any one or more of the methodologiesdiscussed herein.

DETAILED DESCRIPTION

Systems and methods for identifying an individual at a device, thenrecording, storing, and later recognizing that individual and recallingand replaying the recording of the conversation are discussed. In thefollowing description, for purposes of explanation numerous specificdetails are set forth in order to provide a thorough understanding ofsome embodiments of the present disclosure. It will be evident, however,to one skilled in the art that the present disclosure may be practicedwithout these specific details. The following detailed descriptionincludes reference to the accompanying drawings, which form a part ofthe detailed description. The drawings show illustrations in accordancewith example embodiments. These example embodiments, which are alsoreferred to herein as “examples,” are described in enough detail toenable those skilled in the art to practice the present subject matter.The embodiments may be combined, and some embodiments may be utilized,or structural, logical and electrical changes may be made withoutdeparting from the scope of what is claimed. The following detaileddescription is, therefore, not to be taken in a limiting sense, and thescope is defined by the appending claims and their equivalents.

The uses and applications of technology have assimilated into our dailylives in ways we previously could not imagine. Beyond simply superficialadditions, technology has become something that is ingrained in ourday-to-day lives. Wearable devices, such as Google Glass®, offer thepotential to further supplement human social interactions, and offeruseful functionality which may enhance, and support human experiences.In many cases, the intent of functionality offered by wearable devicesis to provide their user with information relevant at the instant.Enabling such functionality in existing devices tends to requireexplicit, non-intuitive commands, or cumbersome and inconvenient steps.This can make for an awkward exchange, and defeat the purpose of thefunctionality offered by the technology. In general, it is desirable toimprove methods for supplementing normal social contexts with technologythat seamlessly integrates into daily social and professionalinteractions.

Aspects of the present disclosure are presented for identifying,recording, inventorying, recalling, and replaying conversations orevents with mobile devices. In an example scenario, a first individualcontrolling a mobile device may engage in a conversation with a secondindividual. In some example embodiments, the mobile device may identifythe second individual by means of facial recognition, voice recognition,or unique Radio Frequency Identifiers (RFID). Upon identifying theindividual, the mobile device may then automatically begin recording theconversation. At the conclusion of the conversation, the mobile devicemay then save the recorded conversation into a dashboard or repositoryfor referencing at the end of the day, end of the conversation, or soforth. Should the first person encounter the second person again at alater time, the mobile device may then recall the previously recordedconversation, through the facial recognition, voice recognition, orunique RFID, and convey the conversation to the first individual suchthat he may be informed and aware of any relevant details he may haveotherwise forgotten. The mobile device may then continue recording andstoring conversations the first individual has with the secondindividual, thereby creating a repository to be referenced at any time.In this way, the recordings of the individual's conversations may beautomatically preserved for future use, without the individual needingto disrupt his or her natural involvement in the engagement through theuse of non-intuitive commands or steps, to explicitly activate andinventory a recording by the mobile device.

Referring to FIG. 1, a block diagram illustrating a mobile device 100 ispresented, according to some example embodiments. The mobile device 100may be configured to detect or identify identifying features of anindividual, according to at least some example embodiments. The mobiledevice 100 may be configured to record a conversation or event with theindividual. Examples of identifying features may include facialfeatures, voice, a unique RFID, barcode, an individual's name, and thelike. Microphone 185 and image recorder 190 may be configured to recordvarious audio recordings and video recordings, respectively. In somecases, the microphone 185 and image recorder 190 may be included into asingle component of mobile device 100, such as an audio/visual (AV)recorder known to those with skill in the art. An application 140running on the mobile device 100 may be configured to instructmicrophone 185 and/or image recorder 190 to automatically record aconversation or event associated with the identified individual. Therecorded conversation or event may be transmitted or stored in arepository for later viewing by the user of the mobile device 100. Thedata of the audio and video recordings may be processed by processor110. The processor 110 may be any of a variety of different types ofcommercially available processors suitable for mobile devices 100 (e.g.,an XScale architecture microprocessor, a Microprocessor withoutInterlocked Pipeline Stages (MIPS) architecture processor, or anothertype of processor). The processor 110 may be configured to operateapplications 140 like the one mentioned above and identify an individualthrough facial recognition, voice recognition, or a unique RFID. Amemory 120, such as a random access memory (RAM), a Flash memory, orother type of memory, is typically accessible to the processor 110. Thememory 120 may be adapted to store an operating system (OS) 130, as wellas application programs 140, such as a mobile application for recordinga conversation or event based on the identified natural gesture ornatural phrase. The processor 110 may be coupled, either directly or viaappropriate intermediary hardware, to a display 150 and to one or moreinput/output (I/O) devices 160, such as a keypad, a touch panel sensor,a microphone, a controller, a camera, and the like. Similarly, in someembodiments, the processor 110 may be coupled to a transceiver 170 thatinterfaces with an antenna 180. The transceiver 170 may be configured toboth transmit and receive cellular network signals, wireless datasignals, or other types of signals via the antenna 180, depending on thenature of the mobile device 100. In this manner, a connection with athird party network such as network 450 of FIG. 4. discussed more below,may be established.

Referring to FIG. 2, other examples of mobile devices that can be usedin aspects of the present disclosure are presented. The devicespresented in FIG. 2 may be wearable devices that are configured toidentify the first or second individual, according to some exampleembodiments. For example, glasses 200 may be specially equipped withmicro viewing technology, one or more microphones, one or more microcameras, and one or more microprocessors that collectively may becapable of identifying the first or second individual in proximity to auser who is wearing glasses 200, and recording events or conversationsincluding those identifying features. Glasses 200 may be similar towearable digital devices such as Google Glass®, and other glasses withdigital technology. As another example, smart watch 210 may also bespecially equipped with one or more microphones, one or more cameras,and one or more microprocessors that collectively may be capable ofidentifying individuals in proximity to a user wearing smart watch 210,and recording events or conversations including those gestures orphrases. As another example, wearable device 220 may be a digital devicewearable around the user's neck. The device 220 may possess similarfunctionality as those described in glasses 200 or smart watch 210.Other example wearable devices can include a Fitbit® and a mobile deviceattached to a shoulder strap. In some example embodiments, a combinationof devices can be configured to facilitate aspects of the presentdisclosure. For example, a first wearable device can be configured toidentify an individual in proximity with the wearer of the device, whilea second wearable device can be configured to record conversations orevents including the identifying features based on the identificationfrom the first wearable device. The two devices could be communicativelycoupled via Bluetooth® or other means apparent to those with skill inthe art. In general, other wearable devices apparent to those with skillin the art and consistent with the disclosures herein may also becapable of performing the functions according to aspects of the presentdisclosure, and embodiments are not so limited.

Referring to FIG. 3, an example scenario 300 utilizing aspects of thepresent disclosure is presented. Here, scenario 300 depicts twoindividuals, a first individual 310 in control of mobile device 320, anda second individual 330. The mobile device 320 may be consistent withmobile device 100, or any of wearable devices 200, 210, or 220. In thisexample, individual 330 may have just approached individual 310 to havea conversation. Individual 310 may desire to be reminded of what hislast conversation with individual 330 pertained to, or may simply desireto record or preserve his conversation with individual 330 withoutdisrupting the flow of the conversation though any interruption toactivate a recording device, or access notes. In some cases, individual310 may desire to simply record and preserve conversations in arepository as a form of keeping notes, or as reminders. Here, mobiledevice 320 would be of assistance to individual 310 in this exchange byfirst being configured to identify an individual in proximity withindividual 310. In some cases, mobile device 320 may be equipped witheither: image recognition software and a camera capable of utilizing theimage recognition software; or speech recognition software, and amicrophone capable of utilizing the speech recognition software. Certainkey features about individual 330 may be programmed or taught to mobiledevice 320, by learning to identify individual 330's facial features orvoice. As another example, individual 310 may desire to record orpreserve parts of a conversation related to a certain subject matter andmay have preprogrammed device 320 to listen for and identify certain keywords or phrases related to the key words or phrases.

Once mobile device 320 has identified an individual, mobile device 320may automatically start recording audio, video, or both simultaneously.Mobile device 320 may therefore capture the conversation. In someexample embodiments, the recording may end after individual 330 has leftthe proximity of individual 310. In other example embodiments, mobiledevice 320 may begin passively recording audio and/or video in a rollingbuffer once an individual has been detected in the proximity ofindividual 310, but before that individual has been identified. Mobiledevice 320 may only store parts of the recording once an individual hasbeen identified through identifying features, in proximity of individual310. For example, while passively recording, mobile device 320 maydetect an individual 330 in proximity with individual 310. In somecases, mobile device 330 may only store the audio and/or videorecordings after detecting and identifying individual 330 withinproximity of individual 310. Mobile device 320 may then either identifythat the individual is individual 330 (an individual who individual 310has previously encountered), or a new individual 340, who individual 310has not encountered yet, with identifiable features which may bepreserved for future identification. In this way, a more completecontext of the conversation may be captured.

The stored recordings of conversations, automatically recorded by mobiledevice 320, may be saved and/or transmitted to a repository configuredto allow quick and easy access for viewing by the user and uploading toother social media by the user. In some example embodiments, mobiledevice 320 may recall, and present to individual 310, notes or completerecordings of prior relevant conversations with an individual, such asindividual 330, upon identifying individual 330 in proximity ofindividual 310, through identification of individual 330's facialfeatures, voice, or unique RFID. For example, upon identifyingindividual 330 in proximity with individual 310, mobile device 320 maybe configured to convey a brief summary containing the key topic ofconversation from individual 310's last encounter with individual 330.The summary may be conveyed to individual 310 in the form of a shortaudio presentation, or a transcription of key words from theconversation in text, or a short video or photo of individual 310's lastconversation with individual 330. The key topic of conversation may bedetermined by frequency of use of a particular word or phrase, or anyother means which a person of skill in the art would utilize todetermine the key topic of conversation. In another embodiment,individual 310 may manually choose certain key words, phrases, or othercriteria, such as the date when the last conversation occurred. Mobiledevice 320 may then convey the requested information to individual 310in an order of most to least relevant, determined by the searchcriteria.

In another example, individual 310 may configure mobile device 320 toremind him of some specific past topic of conversation upon recognizingthat individual 330 is in his proximity. For example, individual 310 maymanually set an alert, either through an intuitive voice command, orthrough a series of steps to be carried out on mobile device 320, whichmay recall a particular fact or piece of information which will bepresented to individual 310 when mobile device 320 identifies individual330 in the proximity of individual 310. In yet another possibleembodiment, an alert may be automatically set by mobile device 320 byaccessing individual 310's mobile calendar, or to-do list. Mobile device320 may be configured to recall past relevant recordings ofconversations with identifiable individuals, upon the identification ofthose individuals. In another example embodiment, mobile device 320could be configured to actively recall any relevant topics of pastconversation stored within the repository, as individual 310 andindividual 330 are engaged in discussion, and convey relevant pieces toindividual 310, based on key words recognized during the conversation.In yet another example embodiment, mobile device 320 could be configuredto actively recall, not only its own recorded past conversations, butmay also conduct a real time search of individual's personal email,social media accounts, or relevant websites. In this way, individual 310may be constantly informed and reminded of relevant information, realtime. An example repository will be described in further detail, below.

Thus, individual 310 can wear or carry mobile device 320, engage in hisinteractions with individual 330, while mobile device 320 can identifyindividual 330, record the conversation, recall relevant informationduring the conversation, and store the recorded conversation in arepository for future reference. In this way, individual 310 can focusall of his attention on individual 330, as well as engage in naturalconversation with individual 330 without having to interrupt hisinteractions in order to activate mobile device 320. Individual 310 maysimply go about his day and interact with whomever he encounters withoutneeding to be mindful of activating mobile device 320 to captureparticular moments of his interaction.

In some example embodiments, mobile device 320 may be a wearable device,such as any of wearable devices 200, 210, or 220. For example, ifindividual 310 was wearing mobile device 320 as a pair of glasses 200,mobile device 320 may be oriented to have one or more cameras directedto capture the field of view of individual 310, and thus may be in asuitable position to identify any individuals in the proximity ofindividual 310. As another example, if individual 310 was wearing mobiledevice 320 as a pendant or necklace, as might be the case with wearabledevice 220, mobile device 320 may also be oriented to capture audiovideo directly in front of individual 310.

Referring to FIG. 4, example scenario 400 is presented, illustrating amore complex system for replaying conversations recorded on mobiledevice 320, according to some example embodiments. In this example,individuals 410 and 420 are both present in a room with an audio/videodisplay. Individual 410 may have in her possession a mobile device 320,which may be consistent with having the capabilities of mobile device320 described in FIG. 3. Thus, mobile device 320 may be capable ofidentifying individuals, recording conversations, and recalling relevantrecordings, just as in FIG. 3. However, additional functionalityaccording to aspects of the present disclosure may also be possible dueto a third-party system surrounding individuals 410 and 420. Forexample, audio/video display 430 may be mounted or positioned in theplace where individuals 410 and 420 are present. Mobile device 320 maybe configured to transmit recorded conversations from the repository,onto audio/video display 430 for the purposes of viewing by individuals410 and 420. In some embodiments, there may be only one audio/videodisplay 430, and in other cases there may be more than two audio/videodisplays 430. Audio/video display 430 may be a part of a third-partynetwork, in the sense that the third-party system or network is notcontrolled or owned by either of individuals 410 or 420. In some exampleembodiments, audio/video display 430 could also be another mobile devicecontrolled by another individual who may also be present in the roomwith individuals 410 and 420. For clarity, individual 410 may beconsidered a first-person entity since she is in control of mobiledevice 320, while individual 420 may be considered a second-personentity, due to interacting with individual 410 and not having control ofmobile device 320. The third-party audio/video display 430 may receiveand replay recorded conversations from mobile device 320 for viewing byall parties present in the room.

In some example embodiment, third party audio/video display 430 may alsohave recording capability itself. For example, individuals 410 and 420may be in a meeting room with several other individuals, where it may bedifficult for mobile device 320 to effectively identify everyone in theroom or record the entirety of the conversation. Audio/video display 430may also include a camera or recording device 435, either incorporatedinto audio/video display 430, or connected otherwise wirelessly or withwires. Once mobile device 320 is configured to replay recordedconversations through audio/video display 430, mobile device 320 mayreceive video and audio from audio/video device 430 in order to identifythe individuals present in the room, and record the conversation whichtakes place in the meeting room to the repository in mobile device 320.In this way, mobile device 320 may be configured to receive audio/videosignals from audio/video display 430, to allow for a more detailed andcomplete recording of the meeting which transpired.

in some example embodiments, a third party server 440 may include thirdparty application 445, with the third party server 440 connected toaudio/video display 430. The third party application may be configuredto control audio/video display 430 to perform the functions describedherein. The audio/video display 430 may be connected wirelessly or viawires to third party server 440. In some example embodiments, therecorded events or moments including the identified natural gesture orphrase may be transmitted from device 320 and saved in third partyserver 440. In other cases, audio/video display 430 may be capable offunctioning independently of third party application 445.

In some example embodiments, third party server 440 may be connected toa network 450, such as the Internet. Through the network 450, therecordings of the conversations captured by mobile device 320 may betransmitted to a central repository viewable by individual 410. Thethird-party system may be able to direct the stored conversation orevent to a repository controlled by individual 410 based on anapplication platform capable of sharing base configurations. Forexample, individual 410 can pre-configure the sharing settings on anapplication platform associated with the repository. The applicationplatform can also allow sharing of conversations or events betweenindividuals or devices recording conversations or events.

In some example embodiments, the conversations recorded by mobile device320 may be transmitted directly to audio/video display 430. The recordedconversations may be transmitted through network 450 via third partyserver 440.

Referring to FIG. 5, example scenario 500 is presented, illustratinganother variant for storing and replaying recorded conversations basedon identified or detected individuals in proximity with an individualwith the described mobile device 320, according to some exampleembodiments. In this example, individuals 510 and 520 are in a classroomwhere individual 510 is diligently taking notes which his professor,individual 520 dictates. Individual 510 may have in his possession andbe in control of mobile device 320, which may operate in the same orsimilar manner as described in FIG. 3 and FIG. 4. In addition, the thirdparty system described in FIG. 4 may also be present to automaticallysave recorded conversations in another designated location, betweenindividuals 510 and 520. Individual 510 may choose to review therecorded conversations as audio or text to be displayed on a personalcomputer 530. For example, mobile device 320 may be configured such thatindividual 510 may designate that individual 520 is his professor, andthat all recorded conversations of individual 520 should be sentdirectly to a folder in his personal computer containing class notesrelevant to individual 520's course. In addition, mobile device 320 mayalso be configured to conduct a search of the repository of recordedconversations, for key words, phrases, or subjects which are topicallyrelevant to the subject matter of individual 520's lecture, and includethose search results in the presented information. In this way, mobiledevice 320 may present recordings of past conversations or lectures withindividual 520 which are relevant to the current lecture. Individual 510may then attend class and supplement his own notes with the recordingscreated by mobile device 320. In another embodiment, mobile device 320may transcribe the audio into text before transmitting audio, text, orboth to personal computer 530.

Referring to FIG. 6, example dashboard 600 illustrates an example formof a repository for receiving and storing the conversations andidentifying features, recorded and identified by the present disclosure.Here, an example list of recorded conversations associated with anindividual 610 and another individual 620 were received and stored indashboard 600 The dashboard 600 could be configured to conveniently andquickly upload any of the stored events to various social media websitesor blogs. The dashboard 600 may allow for preconfigured settings toenable easier access to the social media websites or blogs, such asusername accounts and passwords, as well as specifications as to whatkinds of social media the user has access to. Thus, at the end of theday, or the end of an event, a user can quickly and conveniently accessthe dashboard 600, view what kinds of recordings were capturedautomatically by aspects of the present disclosure, and then access anydesired recordings to be shared by searching. For example, uponsearching for and selecting a number of recordings, the user may chooseto place the recordings, as well as their transcriptions into a documentto be emailed to a group of people. Alternatively, the user may chooseto select bits and pieces of multiple recordings and create a singlecompilation of events, to be shared through the social media of hischoosing. In addition, a user can select their own search criteria whichmay then order the results, and present them to the user in the mostdesirable way. For example, should the user decide that he would likeall results recorded within the last two months related to a particulartopic to be displayed from most recent to least recent, oralternatively, most relevant to the particular topic to less relevant toa particular topic. In this way, the user may select their own orderingcriteria for the search results to more easily and efficiently searchthe repository.

As another example, a journalist may be tasked with researching a storyto be featured on the news. The journalist may visit numerous leads andpeople to be interviewed for the piece. The journalist may be engagedwith meeting a business owner, along with his employees, and patrons ofhis business. The journalist may carry or wear a mobile device, likemobile device 100, 200, 210, 220, or 320, configured to perform variousmethods according to aspects of the present disclosure, includingautomatically identifying individuals within proximity of the device andrecording conversations. Thus, while the journalist conducts herinterviews with individuals she encounters, her mobile device canautomatically identify the individuals, recall relevant informationwhich would be useful to her interview, record the entirety of theinterview, and store the recorded interview in a repository for futureviewing. Then, at the end of the day, the journalist can go through allof the recorded conversations with everyone she may have interviewed viathe repository, an example display of which is shown in FIG. 6. Thejournalist can then select which interviews or selections frominterviews she thinks are particularly noteworthy, and upload thosepreferred recordings to a blog, social media page, or her personalcomputer so she may distribute them to her colleagues as she chooses.

In general, while in some example embodiments, previous conversations ornotes may be recalled upon automatically recognizing an individualassociated with the previous conversation or notes, in other cases, auser may manually recall recorded conversations or events for playbackassociated with an individual, independent of whether that individual isin near proximity to the user. For example, in preparation for abusiness meeting, the user may wish to recall notes from a previousmeeting 15 minutes prior to attending the meeting. The user may recallone or more previous meeting records based on the meeting records beingassociated with an identified person common to the meetings, or in othercases, a group of identified people common to the meetings. The user canthen review the meeting notes before engaging with those sameindividuals in the current meeting.

Referring to FIG. 7, example scenario 700 is presented according to someexample embodiments, illustrating an example of the identification andrecall features as an individual using the device described mayexperience. In this example, individual 710 is in proximity with mobiledevice 320. In the display of mobile device 320, an image of individual710 is presented to the user of the device, with details associated withhis identification by mobile device 320 superimposed adjacent to theimage of individual 710, in readout 720. Readout 720 may includeinformation related to individual 710, such as his name or identifier,details regarding the last time individual 710 was last in proximity ofmobile device 320, a summary related to the topic of the last encounter,or recordings of past conversations related to automatically or manuallydetermined search criteria. This information may be populatedautomatically through mobile device 320, or entered manually by a userof mobile device 320. For example, on a first encounter, if little isknown about an individual in proximity with mobile device 320, mobiledevice 320 may be configured to automatically search through therecorded conversation and populate relevant fields of the readout 720,such as individual 710's name. In another embodiment, mobile device 320may also give its user the option to search through the content of therecordings of conversations with individual 710 by manually searchingthrough search field 730 by key word or search criteria. For example, anindividual using mobile device 320 may wish to search through all therecordings of conversations with individual 710 stored within mobiledevice 320's repository within a two week span.

Referring to FIG. 8, the flowchart illustrates an example methodology800 for identifying individuals, recalling relevant recordedconversations, and recording and storing conversations with a mobiledevice, according to aspects of the present disclosure. The examplemethodology may be consistent with the methods described herein,including, for example, the descriptions in FIGS. 1, 2, 3, 4, 5, 6, and7.

At block 810, a device may identify a first or second individual inphysical proximity with the first individual. The device may be a mobiledevice associated with the first individual, which may be similar tomobile devices 100, 200, 210, 220 or 320. In other cases, the device maybe associated with a third party system separate from both the firstindividual and the second individual, such as through the use of anaudio/video display 430 with recording capability. The device may beconfigured to identify an individual through various facial recognition,voice recognition, unique RFID, barcode, or other similar means apparentto those with skill in the art. The device may be taught or programmedto recognize particular individuals, or particular words or phrases usedin ordinary language.

At block 820, the device may recall past relevant recorded conversationsor outside information based on the second individual recognized inblock 810, and conveys the information to the first individual. In somecases, this can be done by displaying key words or phrases as a form ofa reminder to the first individual, or alternatively as a completerecording or text document. In some embodiments this step may be carriedout at the device, or alternatively may be accomplished by a backendprocessor.

At block 830, the device may record a conversation with the identifiedsecond individual. In some cases, the recording may end after the secondindividual has left the proximity of the first individual. In otherexample embodiments, the device may begin passively recording audioand/or video in a rolling buffer once an individual has been detected inthe proximity of the first individual, but before the individual hasbeen identified. The device may only store parts of the recording oncean individual has been identified in proximity of individual. Forexample, while passively recording, mobile device may detect anindividual in proximity with individual. Mobile device may then storethe audio and/or video recordings after detecting and identifying thesecond individual within proximity of the first individual. The devicemay then determine whether the individual is a previously identifiedindividual, or a new individual, who the first individual has notencountered yet, with identifiable features which may be preserved forfuture identification. In general, block 830 may be consistent with thevarious descriptions herein, including the descriptions in FIGS. 3, 4,and 5.

At block 840, the device may transmit the recording of the conversationto a display system configured to display the recording of theconversation. In some cases, the display system may be a part of thedevice. In other cases, the display system may be a repository, such asa dashboard consistent with the descriptions of FIG. 6. The device mayinclude a transmitter configured to access and transmit the recordedevent.

Referring to FIG. 9, the block diagram illustrates components of amachine 900, according to some example embodiments, able to readinstructions 924 from a machine-readable medium 922 (e.g., anon-transitory machine-readable medium, a machine-readable storagemedium, a computer-readable storage medium, or any suitable combinationthereof) and perform any one or more of the methodologies discussedherein, in whole or in part. Specifically, FIG. 9 shows the machine 900in the example form of a computer system (e.g., a computer) within whichthe instructions 924 (e.g., software, a program, an application 140, anapplet, an app, or other executable code) for causing the machine 900 toperform any one or more of the methodologies discussed herein may beexecuted, in whole or in part.

In alternative embodiments, the machine 900 operates as a standalonedevice or may be connected (e.g., networked) to other machines. In anetworked deployment, the machine 900 may operate in the capacity of aserver machine or a client machine in a server-client networkenvironment, or as a peer machine in a distributed (e.g., peer-to-peer)network environment. The machine 900 may include hardware, software, orcombinations thereof, and may as examples be a server computer, a clientcomputer, a personal computer (PC), a tablet computer, a laptopcomputer, a netbook, a cellular telephone, a smartphone, a set-top box(STB), a personal digital assistant (PDA), a web appliance, a networkrouter, a network switch, a network bridge, or any machine capable ofexecuting the instructions 924, sequentially or otherwise, that specifyactions to be taken by that machine. Further, while only a singlemachine 900 is illustrated, the term “machine” shall also be taken toinclude any collection of machines 900 that individually or jointlyexecute the instructions 924 to perform all or part of any one or moreof the methodologies discussed herein,

The machine 900 includes a processor 902 (e.g., a central processingunit (CPU), a graphics processing unit (GPU), a digital signal processor(DSP), an application specific integrated circuit (ASIC), aradio-frequency integrated circuit (RFIC), or any suitable combinationthereof), a main memory 904, and a static memory 906, which areconfigured to communicate with each other via a bus 908. The processor902 may contain microcircuits that are configurable, temporarily orpermanently, by some or all of the instructions 924, such that theprocessor 902 is configurable to perform any one or more of themethodologies described herein, in whole or in part. For example, a setof one or more microcircuits of the processor 902 may be configurable toexecute one or more modules (e.g., software modules) described herein.

The machine 900 may further include an audio/visual recording device928, suitable for recording audio and/or video. The machine 900 mayfurther include a video display 910 (e.g., a plasma display panel (PDP),a light emitting diode (LED) display, a liquid crystal display (LCD), aprojector, a cathode ray tube (CRT), or any other display capable ofdisplaying graphics or video). The machine 900 may also include analphanumeric input device 912 (e.g., a keyboard or keypad), a cursorcontrol device 91.4 (e g., a mouse, a touchpad, a trackball, a joystick,a motion sensor, an eye tracking device, or other pointing instrument),a storage unit 916, a signal generation device 918 (e.g., a sound card,an amplifier, a speaker, a headphone jack, or any suitable combinationthereof), and a network interface device 920.

The storage unit 916 includes the machine-readable medium 922 (e.g., atangible and non-transitory machine-readable storage medium) on whichare stored the instructions 924 embodying any one or more of themethodologies or functions described herein, including, for example, anyof the descriptions of FIGS. 1, 2, 3, 4, 5, 6, and/or 7. Theinstructions 924 may also reside, completely or at least partially,within the main memory 904, within the processor 902 (e.g., within theprocessor's cache memory), or both, before or during execution thereofby the machine 900. The instructions may also reside in the staticmemory 906.

Accordingly, the main memory 904 and the processor 902 may be consideredmachine-readable media 922 (e.g., tangible and non-transitorymachine-readable media). The instructions 924 may be transmitted orreceived over a network 926 via the network interface device 920. Forexample, the network interface device 920 may communicate theinstructions 924 using any one or more transfer protocols (e.g.,Hypertext Transfer Protocol (HTTP)). The machine 900 may also representexample means for performing any of the functions described herein,including the processes described in FIGS. 1, 2, 3, 4, 5, 6, and/or 7.

In some example embodiments, the machine 900 may be a portable computingdevice, such as a smart phone or tablet computer, and have one or moreadditional input components (e.g., sensors or gauges), not shown.Examples of such input components include an image input component(e.g., one or more cameras), an audio input component (e.g., amicrophone), a direction input component (e.g., a compass), a locationinput component (e.g., a global positioning system (GPS) receiver), anorientation component (e.g., a gyroscope), a motion detection component(e.g., one or more accelerometers), an altitude detection component(e.g., an altimeter), and a gas detection component (e.g., a gassensor). Inputs harvested by any one or more of these input componentsmay be accessible and available for use by any of the modules describedherein.

As used herein, the term “memory” refers to a machine-readable medium922 able to store data temporarily or permanently and may be taken toinclude, but not be limited to, RAM, read-only memory (ROM), buffermemory, flash memory, and cache memory. While the machine-readablemedium 922 is shown in an example embodiment to be a single medium, theterm “machine-readable medium” should be taken to include a singlemedium or multiple media (e.g., a centralized or distributed database,or associated caches and servers) able to store instructions 924. Theterm “machine-readable medium” shall also be taken to include anymedium, or combination of multiple media, that is capable of storing theinstructions 924 for execution by the machine 900, such that theinstructions 924, when executed by one or more processors of the machine900 (e.g., processor 902), cause the machine 900 to perform any one ormore of the methodologies described herein, in whole or in part.Accordingly, a “machine-readable medium” refers to a single storageapparatus or device, as well as cloud-based storage systems or storagenetworks that include multiple storage apparatus or devices. The term“machine-readable medium” shall accordingly be taken to include, but notbe limited to, one or more tangible (e.g., non-transitory) datarepositories in the form of a solid-state memory, an optical medium, amagnetic medium, or any suitable combination thereof.

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationsmay be implemented as a combined structure or component Similarly,structures and functionality presented as a single component may beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Certain embodiments are described herein as including logic or a numberof components, modules, or mechanisms. Modules may constitute softwaremodules (e.g., code stored or otherwise embodied on a machine-readablemedium 922 or in a transmission medium), hardware modules, or anysuitable combination thereof. A “hardware module” is a tangible (e.g.,non-transitory) unit capable of performing certain operations and may beconfigured or arranged in a certain physical manner. In various exampleembodiments, one or more computer systems (e.g., a standalone computersystem, a client computer system, or a server computer system) or one ormore hardware modules of a computer system (e.g., a processor or a groupof processors 902) may be configured by software (e.g., an application140 or application portion) as a hardware module that operates toperform certain operations as described herein.

In some embodiments, a hardware module may be implemented mechanically,electronically, or any suitable combination thereof. For example, ahardware module may include dedicated circuitry or logic that ispermanently configured to perform certain operations. For example, ahardware module may be a special-purpose processor, such as a fieldprogrammable gate array (FPGA.) or an ASIC. A hardware module may alsoinclude programmable logic or circuitry that is temporarily configuredby software to perform certain operations. For example, a hardwaremodule may include software encompassed within a general-purposeprocessor 902 or other programmable processor 902. It will beappreciated that the decision to implement a hardware modulemechanically, in dedicated and permanently configured circuitry, or intemporarily configured circuitry (e.g., configured by software) may bedriven by cost and time considerations.

Accordingly, the phrase “hardware module” should be understood toencompass a tangible entity, and such a tangible entity may bephysically constructed, permanently configured (e.g., hardwired), ortemporarily configured (e.g., programmed) to operate in a certain manneror to perform certain operations described herein. As used herein,“hardware-implemented module” refers to a hardware module. Consideringembodiments in which hardware modules are temporarily configured (e.g.,programmed), each of the hardware modules need not be configured orinstantiated at any one instance in time. For example, where a hardwaremodule comprises a general-purpose processor 902 configured by softwareto become a special-purpose processor, the general-purpose processor 902may be configured as respectively different special-purpose processors(e.g., comprising different hardware modules) at different times.Software (e.g., a software module) may accordingly configure one or moreprocessors 902, for example, to constitute a particular hardware moduleat one instance of time and to constitute a different hardware module ata different instance of time.

Hardware modules can provide information to, and receive informationfrom, other hardware modules. Accordingly, the described hardwaremodules may be regarded as being communicatively coupled. Where multiplehardware modules exist contemporaneously, communications may be achievedthrough signal transmission (e.g., over appropriate circuits and buses)between or among two or more of the hardware modules. In embodiments inwhich multiple hardware modules are configured or instantiated atdifferent times, communications between such hardware modules may beachieved, for example, through the storage and retrieval of informationin memory structures to which the multiple hardware modules have access.For example, one hardware module may perform an operation and store theoutput of that operation in a memory device to which it iscommunicatively coupled. A further hardware module may then, at a latertime, access the memory device to retrieve and process the storedoutput. Hardware modules may also initiate communications with input oroutput devices, and can operate on a resource (e.g., a collection ofinformation).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors 902 that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors 902 may constitute processor-implementedmodules that operate to perform one or more operations or functionsdescribed herein. As used herein, “processor-implemented module” refersto a hardware module implemented using one or more processors 902.

Similarly, the methods described herein may be at least partiallyprocessor-implemented, with a processor 902 being an example ofhardware. For example, at least some of the operations of a method maybe performed by one or more processors 902 or processor-implementedmodules. As used herein, “processor-implemented module” refers to ahardware module in which the hardware includes one or more processors902. Moreover, the one or more processors 902 may also operate tosupport performance of the relevant operations in a “cloud computing”environment or as a “software as a service” (SaaS). For example, atleast some of the operations may be performed by a group of computers(as examples of machines 900 including processors), with theseoperations being accessible via a network 926 (e.g., the Internet) andvia one or more appropriate interfaces (e.g., an application programinterface (API)).

Some portions of the subject matter discussed herein may be presented interms of algorithms or symbolic representations of operations on datastored as bits or binary digital signals within a machine memory (e.g.,a computer memory). Such algorithms or symbolic representations areexamples of techniques used by those of ordinary skill in the dataprocessing arts to convey the substance of their work to others skilledin the art. As used herein, an “algorithm” is a self-consistent sequenceof operations or similar processing leading to a desired result. In thiscontext, algorithms and operations involve physical manipulation ofphysical quantities. Typically, but not necessarily, such quantities maytake the form of electrical, magnetic, or optical signals capable ofbeing stored, accessed, transferred, combined, compared, or otherwisemanipulated by a machine 900. It is convenient at times, principally forreasons of common usage, to refer to such signals using words such as“data,” “content,” “bits,” “values,” “elements,” “symbols,”“characters,” “terms,” “numbers,” “numerals,” or the like. These words,however, are merely convenient labels and are to be associated withappropriate physical quantities.

Unless specifically stated otherwise, discussions herein using wordssuch as “processing,” “computing,” “calculating,” “determining,”“presenting,” “displaying,” or the like may refer to actions orprocesses of a machine 900 (e.g., a computer) that manipulates ortransforms data represented as physical (e.g., electronic, magnetic, oroptical) quantities within one or more memories (e.g., volatile memory,non-volatile memory, or any suitable combination thereof), registers, orother machine components that receive, store, transmit, or displayinformation. Furthermore, unless specifically stated otherwise, theterms “a” or “an” are herein used, as is common in patent documents, toinclude one or more than one instance. Finally, as used herein, theconjunction “or” refers to a non-exclusive “or,” unless specificallystated otherwise.

The following enumerated descriptions define various example embodimentsof methods, machine-readable media 922, and systems (e.g., apparatus)discussed herein:

1. A computer implemented method comprising:

-   identifying, in a first encounter, at a device, a first person, or a    second person or entity in physical proximity with the first person;-   recording, at the device, a conversation or event of the first    encounter with the identified first person, or the second person or    entity;-   transmitting the recording of the conversation or event to a memory    repository configured to replay the conversation;-   automatically recognizing, in a second encounter, at the device, the    first person, or the second person or entity;-   recalling based on the automatic recognizing, at the device, the    recorded conversation or event of the first encounter with the first    person or second person or entity; and-   conveying, at the device, the recorded conversation or event to the    first person.

2. The method of description 1, wherein the device organizes dataassociated with the second person or entity, based on identifyingfeatures;

-   wherein the identifying features include facial features, voice,    RFID, barcode, or fingerprint.

3. The method of description 1, wherein the device includes a thirdparty device controlled by a third party that is separate from both thefirst person and the second person or entity;

-   wherein the third party device replays the recording of the    conversation or event from the first person device.

4. The method of description 1, herein the device conveys the recordingof the conversation or event to the first person through text.

5. The method of description 1, wherein the device recalls additionalpast conversations with the recognized first person or second person orentity based on the automatic recognizing of the first person or thesecond person;

-   wherein the recordings are recalled based on the conversations or    events that are most topically relevant to a most recent    conversation or event with the first person, or the second person or    entity.

6. The method of description 5, further comprising generating anordering of the recorded conversation or event from most to leastrelevant, at the device, based on an ordering criterion;

-   conveying the recording or event of conversations in an order based    on the ordering criterion.

The method of description 1, further comprising sharing the recordingsof the conversation or event with the second person or entity;

-   wherein the conversation or event is shared through email, social    media, or mobile messaging.

7. An apparatus comprising an input interface, an output interface, andat least one processor configured to perform any of the descriptions indescriptions 1 through 6.

8. A computer-readable medium embodying instructions that, when executedby a processor, perform operations comprising any of the descriptions indescriptions 1 through 6.

9. An apparatus comprising means for performing any of the descriptionsin descriptions 1 through 6.

What is claimed is:
 1. A method comprising: detecting a Radio FrequencyIdentifier (RFID) of a first device of a first person in proximity witha second device of a second person; identifying the first person basedon attributes of the first person and the RFID of the first device;initiating recording a conversation between the first person and thesecond person to a memory location associated with the first person, inresponse to the identifying the first person; determining that the RFIDof the first device is not within the proximity of the second device;and ceasing recording the conversation between the first person and thesecond person.
 2. The method of claim 1, wherein the identifyingfeatures include one or more facial features, voice data, a radiofrequency identifier (RFID), a barcode, or a fingerprint.
 3. The methodof claim 1, wherein the method further comprises: transmitting theconversation to a third party device controlled by a third party that isseparate from both the first person and the second person.
 4. The methodof claim 1, wherein the method further comprises conveying theconversation to the second person.
 5. The method of claim 4, wherein theconveying the conversation to the second person includes: transcribingthe conversation into text; and causing display of the text at thedevice of the second person.
 6. The method of claim 1, wherein themethod further comprises: recalling a past conversation between thefirst person and the second person in response to the identifying thefirst person based on the identifying features, the past conversationhaving occurred previously to the detecting the first person inproximity with the device of the second person; and conveying the pastconversation to the second person.
 7. The method of claim 6, wherein therecalling the past conversation between the first person and the secondperson includes: identifying the past conversation among a set of pastconversations based on the identifying the first person and theidentifying the key word, wherein the past conversation includes the keyword.
 8. The method of claim 1, wherein the method further comprisessharing the conversation with the first person, wherein the sharing theconversation includes: detecting a device associated with the firstperson; and transmitting the conversation to the device associated withthe first person via a text message or email.
 9. A system comprising:one or more processors; and a non-transitory memory storing instructionsthat configure the one or more processors to perform operationscomprising: detecting a RFID of a first person in proximity with adevice of a second person; identifying the first person based onidentifying features of the first person, the identifying featuresincluding a voice of the first person and the RFID of the first person;retrieving a previous recorded conversation between the second personand the first person in response to the identifying the first person;identifying a key word within the previous recorded conversation, theidentifying the key word based on a frequency of the key word in theprevious recorded conversation; passively recording a conversationbetween the first person and the second person to a rolling buffer;identifying the key word in the conversation between the first personand the second person; recording the conversation to a memory repositoryin real time in response to identifying the key word; and sharing therecording of the conversation with the second person.
 10. The system ofclaim 9, wherein the identifying features include one or more facialfeatures, voice data, a radio frequency identifier (RFID), a barcode, ora fingerprint.
 11. The system of claim 9, wherein the instructions causethe system to perform operations further comprising: transmitting theconversation to a third party device controlled by a third party that isseparate from both the first person and the second person.
 12. Thesystem of claim 8, wherein the device conveys the recordings of theconversations to the first person through transcribing the recordinginto text.
 13. The system of claim 8, wherein the instructions cause thesystem to perform operations further comprising conveying theconversation to the second person.
 14. The system of claim 13, whereinthe conveying the conversation to the second person includes;transcribing the conversation into text; and causing display of the textat the device of the second person.
 15. The system of claim 9, whereinthe instructions cause the system to perform operations furthercomprising: recalling a past conversation between the first person andthe second person in response to the identifying the first person basedon the identifying features, the past conversation having occurredpreviously to the detecting the first person in proximity with thedevice of the second person; and conveying the past conversation to thesecond person.
 16. The system of claim 15, wherein the recalling thepast conversation between the first person and the second personincludes: identifying the past conversation among a set of pastconversations based on the identifying the first person and theidentifying the key word, wherein the past conversation includes the keyword.
 17. The system of claim 9, wherein the instructions cause thesystem to perform operations further comprising sharing the conversationwith the first person, and wherein the sharing the conversationincludes: detecting a device associated with the first person; andtransmitting the conversation to the device associated with the firstperson via a text message or email.
 18. A non-transitorycomputer-readable medium embodying instructions that, when executed by aprocessor, perform operations comprising: detecting a RFID of a firstperson in proximity with a device of a second person; identifying thefirst person based on identifying features of the first person, theidentifying features including a voice of the first person and the RFIDof the first person; retrieving a previous recorded conversation betweenthe second person and the first person in response to the identifyingthe first person; identifying a key word within the previous recordedconversation, the identifying the key word based on a frequency of thekey word in the previous recorded conversation; passively recording aconversation between the first person and the second person to a rollingbuffer; identifying the key word in the conversation between the firstperson and the second person; recording the conversation to a memoryrepository in real time in response to identifying the key word; andsharing the recording of the conversation with the second person. 19.The non-transitory computer-readable medium of claim 18, wherein theidentifying features include one or more facial features, voice data, aradio frequency identifier (RFID), a barcode, or a fingerprint.
 20. Thenon-transitory computer-readable medium of claim 18, wherein theoperations further comprise: transmitting the conversation to a thirdparty device controlled by a third party that is separate from both thefirst person and the second person.